An intelligent decision supporting system for international classification of functioning, disability, and health

Abstract

Abstract Background In recent years, the population structure in Taiwan has changed so dramatically. Based on concerns of social welfare issues, Taiwanese government began to seek principles for assessment of disability. After seven years of carefully evaluation, the World Health Organization’s International Classification of Functioning, Disability, and Health (Abbreviated to ICF) is officially adopted as Taiwan’s assessment standard while most of the assessment procedures of ICF are sophisticated, and time consuming. In this paper, we propose a sensor based decision supporting system for ICF. Our prototype system aims to reduce the burden of medical staffs, and to assist subjects to perform the assessments. Methods This paper integrate multiple devices including ASUS XtionTM, temperature/acceleration/gyro sensors on Arduino, and Zigbee to measure the mobility of limbs and joints. The subject’s log of assessments is then recorded in the database so that the medical staffs can remote-monitor the co ndition of subjects immediately, and analyze the results later. Additionally, in our system, a user-friendly interface is implemented for the detection of dementia. Results In this paper, three experiments have been conducted for different purpose. The experiment was conducted to compare the variation between thermometer and our device. Moreover, we invited 20 elders aged for 65 to 80 to use our system and all of them gave positive feedback. Two elders were invited to perform full assessment for dementia and the results show that both of them didn’t have sign of dementia. Also, the assessment of joint movement was performed by a 67 year-old elder and the result shows that the elder had well physical function and could take care of daily life. Conclusions The proposed system has potential for aiding users to perform the ICF testing better and provide benefits to medical staffs and society. With current technology, integration between sensor network systems and artificial intelligence approaches will more and more important. We develop a simple interface for user to manipulate and perform the ICF assessment. In addition, the early detection of dementia likely has the potential to provide patients with an increased level of precaution, which may improve quality of life.